Intelligent Metasurfaces Revolutionize Wireless Communication Through Environmental Reshaping
TL;DR
Intelligent metasurfaces revolutionize wireless communication, offering a cost-effective and efficient way to reshape the environment.
Intelligent metasurfaces with deep learning algorithms actively adapt to wireless environments, offering practical solutions for signal processing and transmission.
Intelligent metasurfaces pave the way for greener wireless communication, reducing hardware expenditure and energy consumption for a sustainable future.
Scientists at Zhejiang University explore the potential of intelligent metasurfaces in reshaping wireless communication through innovative research and experimental implementations.
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Intelligent metasurfaces represent a transformative approach to wireless communication by actively managing the entire communication environment rather than passively adapting to surroundings. This technology, composed of subwavelength passive or active meta-atoms, offers a green alternative to conventional methods that require massive deployment of active nodes to compensate for propagation loss. The traditional approach necessitates high hardware expenditure, energy consumption, and maintenance costs while creating complicated network interference issues that have long challenged the wireless communication industry.
Researchers from Zhejiang University, led by Professor Hongsheng Chen and Professor Chao Qian, have provided a comprehensive overview of recent advancements in intelligent metasurfaces for free management of wireless communication environments. Their work, published in Light Science & Applications, details how these surfaces can facilitate wireless communication through three primary functions: signal relay, signal transmission, and signal processing. The integration of various deep learning algorithms enables intelligent metasurfaces to adapt to ever-changing environments without human intervention, marking a significant departure from conventional passive adaptation techniques.
The research begins with channel modeling and surveys active approaches to achieve tunable metasurfaces at microwave frequencies. Special attention is given to deep learning algorithms for forward prediction of electromagnetic scattering and inverse design of metasurface distribution, which are crucial for achieving true intelligence in these systems. The study provides experimental implementations demonstrating how to reshape wireless communication environments and, more significantly, how to physically process signals at the metasurface level.
Funding for this research was provided through multiple grants, including the Key Research and Development Program of the Ministry of Science and Technology under Grant Nos. 2022YFA1404704, 2022YFA1405200, and 2022YFA1404902, along with support from the National Natural Science Foundation of China and the Key Research and Development Program of Zhejiang Province. The original research can be accessed at https://doi.org/10.1038/s41377-024-01729-2.
From an electromagnetic perspective, the researchers identify key future directions where substantial impact is expected in the coming years and highlight imminent challenges that hinder further off-the-shelf applications. The evolution of metasurfaces from passive to active and finally to intelligent configurations represents a paradigm shift in wireless communication technology, offering solutions to the longstanding challenge of pursuing higher data rates with limited spectral resources while addressing environmental and economic concerns.
Curated from 24-7 Press Release


